2022-05-09

Gene expression and flight performance analysis for different monarch populations

Analysis of two monarch populations, East and West:

  • Differences in flight performance
  • Correlation in the genetic profiles to check for distinction in the two populations
Fig.1-Map showing sampling locations

Process of the project

Steps followed in the duration of this project-

Dataset

This is the final joined dataset we used for our analysis

## # A tibble: 6 × 21
##   ID    Gene_379 Gene_203 Gene_C2 Gene_C4 Gene_C5 Gene_C7 Sex   Population premass postmass weightloss time.sec time.min
##   <chr>    <dbl>    <dbl>   <dbl>   <dbl>   <dbl>   <dbl> <chr> <chr>        <dbl>    <dbl>      <dbl>    <dbl>    <dbl>
## 1 FL35     -5.74    -5.53   -4.80   -4.46   -4.42   -4.77 F     east         0.470    0.462      -5.43    1798.    30.0 
## 2 FL72     -6.21    -6.37   -4.73   -4.46   -4.46   -5.02 F     east         0.540    0.524      -4.99    1311.    21.9 
## 3 FL74     -4.86    -4.59   -2.65   -2.61   -2.90   -2.84 F     east         0.522    0.511      -5.09    1711.    28.5 
## 4 FL75     -6.14    -6.31   -4.84   -4.34   -4.44   -4.87 F     east         0.564    0.540      -4.97    1799.    30.0 
## 5 FL79     -4.40    -4.18   -3.01   -2.77   -3.18   -2.98 F     east         0.581    0.580      -5.36     306.     5.09
## 6 FL05     -6.00    -6.18   -4.94   -4.79   -4.25   -4.71 M     east         0.499    0.493      -4.97     857.    14.3 
## # … with 7 more variables: distance <dbl>, averagevelocity <dbl>, maxvelocity <dbl>, power <dbl>, Area <dbl>,
## #   PC1_wing_size <dbl>, PC2_wing_shape <dbl>

Methods

  • Data augmentation - new variables created: efficiency and distance class
  • Plot visualizations - plots to visualize our data and generally understand them
  • Statistical analysis:
    • Visualizations of augmented variables
    • Logistic regression
    • PCA analysis and clustering

Results : Data exploration

plots = map(numeric_ones, 
            ~datadistribution_plot("Population",
                                   ., 
                                   my_data_clean))

Fig.2-Violin plot of average velocity

Fig.3-Violin plot of weight loss

Results : Data visualization

We performed T-test on flight performance variables and observed the following:

  • Flight distance and duration are higher for Eastern monarchs which fly longer distances
  • Flight power and efficiency are higher for Western monarchs which fly relatively shorter distances
Fig.4-Analysis of flight performance

Results : Data visualization

  • Genes 203 and 379 are heavily downregulated in both populations

  • Genes C2, C4, C5 and C7 seem to be comparatively more downregulated in Eastern Monarchs

    Fig.5-Box plots of gene expression

    Fig.6-Heat maps of gene expression

Results : Modelling

Logistic regression to determine significance of gene expression on populations

  • All genes show no significant relation to the differences between Eastern and Western Monarchs
  • Gene C5 which is the myosin heavy chain gene, shows comparatively higher association with populations
Fig.7-Logistic regression on gene expression

Results : Modelling

With PCA and clustering on the data, we obtained the following results-

PCA population

PCA distance class

Discussion

From our analysis we can conclude the following about the Eastern and Western Monarchs:

  • There is a significant difference in flight performance between the two populations
  • There are no genetic distinction between the two populations






Thank you :)